Investors have long sought in vain a method for determining the future relative value of an investment from an analysis of its relative value in a past period. This is an invention to provide such an evaluative tool for book-valued investments.
It is convention in the investment industry to value investments by their investment performance over time, and to make judgments as to the relative value of investments in terms of differences in investment performance between investments whose performance have historically reacted similarly to changes in market conditions. Populations of these similar investments are grouped as ‘asset classes’, and it has become common practice to base the construction of these asset classes on the tenets of Modern Portfolio Theory (MPT), whereby populations of investments are grouped by virtue of the characteristic of having uniquely similar patterns and levels of investment risk in a past time period.
It has also become common practice to summarize the average performance characteristics of such asset classes in terms of a ‘market’ or ‘securities’ line—a division into halves of the distribution of investment performance found among an asset class population, constructed under the tenets of the Capital Assets Pricing Model (CAPM). The return for an individual investment within the asset class is compared to the return as modeled by this market line and the difference represents the value of the investment's performance relative to the asset-class average. This incremental value is defined within the industry as either an investment's ‘differential return’ or its ‘alpha’.
Economists have long sought to use the differences in value found by an investment's relationship to its market line in a prior period (‘evaluation period’) to signal a reliable difference in value in a future period (‘selection period’). They have been frustrated by the weak and conflicting results achieved by this evaluative methodology.
It is the common practice within the investment management industry to define investment performance in terms of risk and reward. Dr. Harry Markowitz provided the generally accepted definition of this term, in his thesis, “Modern Portfolio Theory” (MPT), proposing that the value of an investment to its investors was found in the tradeoff between the return generated by the investment over time and the risk of that investment. Markowitz, 1952.
In MPT, Markowitz proposed a method to measure this tradeoff, creating definitions for its component parts that could be quantified mathematically. He defined investment return as the average of the periodic returns of an investment over time (‘mean’), and investment risk as the volatility of those periodic returns over that time period (‘variance’). It has become convention to calculate investment performance in terms of this ‘mean-variance’ relationship and document performance in terms of a ‘mean-variance graph’ as illustrated in prior art FIG. 1.
Markowitz also recommended a strategy for maximizing the available performance of an investment portfolio. His MPT provided that mathematical proof that the efficiency of such a portfolio could be maximized if it were made up of investment assets that provided different and offsetting patterns of periodic-return volatility over time. He offered a procedure for quantifying this point—an algorithm to calculate portfolio-level investment risk from the pair-wise covariant relationship between the investment risk of its component investments.
Such an algorithm produces a ‘costly’ calculation—the number of pair-wise relationships that need to be calculated increases exponentially as a function of the number of investment alternatives considered. This shortcoming has led to the practice that such ‘asset-allocation strategies’ be computed from ‘a small handful of investment alternatives’. It has become prevailing industry practice to cast asset-allocation strategies in terms of this small number of investment market alternatives, constructing a finite number of ‘asset-classes’ from populations of individual investments that have historically demonstrated a uniquely common pattern of investment risk and using the average investment performance of these asset-class populations or of an asset class-index as the proxy for the effect of combining individual investments within an allocation strategy.
The industry of investment management entails the management of investment portfolios. Based on the structures promulgated by the tenets of MPT, the investment manager's job is comprised of (2) functions. First, an asset-allocation strategy must be selected in terms of the combination of a small number of broad asset classes whose performance is representative of a large population of alternative investments. Next, one or more individual investments must be selected from within each selected asset class with which to implement this strategy.
The value of the allocation strategy selected is based on the extent to which the future risk of the strategy remains a match for the risk tolerance of the portfolio holder and the future performance of that strategy betters that of alternative strategies at a like level of risk. The value of the investments selected is dependent on the extent by which their future investment performance surpasses the average of their asset-class peers.
The present invention, as will be described in detail below, is an evaluative process that pertains to the second of these (2) management functions—the selection of investments within an asset-class. Its use is limited to those asset-classes that are made up of book-valued investments. The primary market for book-valued investments is the one for book-valued collective investment funds—privately-managed investment portfolios, collective and common trusts, unit-investment trusts, separate accounts, open-ended investment companies (mutual funds), and other such collections of investment securities whose valuation is solely related to the net-asset value of the securities within the collection. By far, the largest and most visible market for these book-valued collective investment funds is the mutual fund market, and the utility of this invention is illustrated in terms of the performance characteristics of that market since 1991.
It has become convention to value the investments within an asset-class by virtue of differences in investment performance in a prior time period—most usually a prior period that ends at the date at which the evaluation takes place. Industry marketing literature is replete with claims from investment providers that tout their prior-period ‘track-record’ vis-à-vis their asset-class peers or against an index that is thought to be emblematic of the average performance of those peers.
Economists have sought to validate this valuation process by finding evidence of the persistency of these performance differences into a future period—to find that the ‘winners’ of an asset class so identified in the past, remain winners into the future. They have been frustrated in their efforts in that the empirical evidence of such persistency collected using existing analytical processes has been weak and conflicting. Notwithstanding the lack of evidence confirming that differences in past performance provides a useful signal of differences in future performance, the practice of evaluating the worthiness of investments based on the past strength of their performance relative to their asset-class peers prevails among industry practitioners and investors.
Therefore, there is a need for a corrective process that improves on the existing procedures in general use for valuing the past performance of book-valued investments within an asset-class. The present invention solves for the conundrum posed by past analyses of empirical data regarding the persistency of performance differences, producing, as a narrow application, an evaluative technique of practical relevance for those practitioners that believe they possess special knowledge of future market trends. This basic process is further enhanced to provide a wider application—a method of evaluating differences in past performance that has practical relevance for those practitioners that profess no special knowledge or ability to predict future market trends, and that require a valuation procedure that retains its legitimacy regardless of the future path of market conditions.
This invention is based on and relates to (2) insights regarding the operation of book-valued asset-class populations of investments that are novel and unique. The claim of uniqueness made for this invention lies in the novelty of these insights, and their proof is contained in a review of the academic and industry-related literature since the introduction of MPT. Its utility is demonstrated through the analysis of the differences in future performance between segments of conventional asset-class populations of mutual funds that can be identified through these processes for quarterly evaluation periods December 1991 and June 2002.
Differences in investment performance between mutual funds within an asset-class have historically been documented through an analysis based on the tenets of the Capital Assets Pricing Model (CAPM). [Sharpe, 1960] This is the existing evaluative framework. This model is central to processes in use in the investment industry in that it provides the theoretical underpinning for using an asset-class average or class-index as the proxy for a population of investment alternatives within the analytical processes of MPT.
Sharpe's CAPM defines the average performance for a population of asset-class funds as a linear relationship derived from a point of zero investment risk, through a point of average investment risk and return for the population and extending across the range of risk available within the asset-class population. This ‘market line’ or ‘securities line’ summarizes the average investment performance found within a population of investments whose individual performance is assumed to form a normal or otherwise stable, symmetric distribution around this line.
Within this model, a fund whose past performance has been found to reside above the market line on a mean-variance graph is generally evaluated as ‘strong’; a fund whose performance resides below the market line is graded as ‘weak’. Prior art FIGS. 2 and 3 illustrate the CAPM view of an asset-class population in terms of the mean-variance paradigm. According to FIG. 2 and under the tenets of the CAPM, the average investment performance for an asset class population of investments is represented by a ‘market line’. On the mean-variance graph of FIG. 2, this market line is a straight line drawn from a point of zero risk (y-axis), through the point of average risk and return for the asset class and across the breadth of risk present in the asset class population.
For purposes of illustration, the charts used in the industry typically follow the convention of color-coding populations of funds whose average investment performance is thought to be ‘strong’ relative to their class peers as ‘green (G)’ (referred to as “G” herein); those whose average performance is considered ‘weak’ relative to their peers as ‘red’ (referred to as “R” herein); and populations whose average performance is not significantly different from the class average of their peers as ‘yellow’ (referred to as Y herein) including yellow 1 (Y1) and yellow 2 (Y2). FIG. 3 introduces this coding convention.
The vertical distance from a market line in FIG. 3 is the measurement of an investment's ‘differential return’ for an asset-class population whose investment risk is measured in terms of the standard deviation of their periodic returns. This vertical distance is termed an investment's ‘alpha’ for those asset-class populations whose investment risk is measured in terms of the covariance of their periodic returns (‘beta’).
Within the analytical structure of the CAPM, an investment's performance in a prior time period is considered ‘strong’ if its point when plotted on a mean variance graph resides above the market line (G). Its performance is ‘weak’ if its point resides below the line (R) FIG. 3.
However, there are issues with the known existing evaluative framework. For it to be of practical use, the evaluation of a fund's performance relative to its asset-class peers in a past-period must have some bearing on the fund's expected investment performance relative to those peers into the future.
Since the inception of CAPM, economists have sought to find a process for sectioning the distribution of past-period investment performance for an asset-class population of funds in a manner that would reveal differences in their future performance. This effort has historically centered around ‘a search for the holy-grail’ which is a method of predictive selection that would consistently signal which fund managers would be ‘the winners’ of a future period. Their methods have been based on the concept that the successful track record of fund managers in a past period should persist—that ‘winners repeat’. Thus said, the segmentation strategies employed have revolved around dividing an asset-class population between its strongest and weakest members in terms past-period investment performance and looking for a pattern of persistent differences in investment performance from these segments into the future.
Economists have been singularly unsuccessful in this pursuit. Selecting for those funds whose past performance has been most positive (the top 100 performers, for example) has generated a mixed picture. There exist a host of studies where analysts have found that rather than signaling future strength, membership in the strongest-performing group in a past period ensures only a marginal chance of a positive future at best, and in most cases, results in negative future performance differences. [Jensen, 1968], [Grant, 1978], [Malkiel, 1995], [Sharpe, 1996]
Other studies, taken over different analysis periods offer somewhat conflicting conclusions—finding positive differences in investment performance within an asset-class of funds that can persist, albeit for only short time-periods into the future and under special market conditions. [Grinblatt, 1992], [Hendricks, 1993], [Goetzmann, 1994], [Brown, 1995], [Wermers, 1996], [Cahart, 1997]
The common thread in these analyses—the one conclusion of practical use—has been the finding that the section of a population that contains the worst-performing funds for a past period persists in being among the worst-performers of a future period.
“The added return in the past, because of a relatively small degree of persistence, is a pretty rotten indicator unless it is big and negative.” [Tanous, p.99, 1997]
Frustrated at finding a valuable indicator among differences in past-period investment performance, with the exception of identifying the losers, economists have taken to using their evaluative results to denigrate the efforts of their peers that just happen to be managers of mutual funds.
“The year-to-year ranking of most mutual funds appear largely random . . . the only significant persistence not explained is concentrated in strong under-performance by the worst-return mutual funds . . . the[se] results do not support the existence of skilled or informed mutual fund managers.” [Cahart, 1997]
This regression in the utility of evaluative processes based on past-period differences in asset-class performance to a tool for the parochial infighting among practicing economists does not create any value for the investor attempting to evaluate the efficiency of the management of their portfolio holdings. What is needed is a renovation of the process to be of practical service to that investor.
It is reasonable for an investor to have an interest in identifying how their investments within an asset class, whether structured as a private portfolio or one or more other types of book-valued collective funds, have performed relative to their peers. It is also reasonable for that investor to have an expectation that the prevailing convention of utilizing differences in past performance to value funds holds some significance for signaling differences in future performance. The objective of this invention is provide for these reasonable needs—to provide a renovated process of identifying differences in past-period performance among book-valued collective investment funds that does have a relevance to future differences to be found in an asset-class population of these funds.